Tag: Large Language Model
All the articles with the tag "Large Language Model".
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REARANK: Reasoning Re-ranking Agent via Reinforcement Learning
Published: at 11:19 AM
90.58 🤔本文提出REARANK，一种基于强化学习的列表式重排序代理，通过显式推理和数据增强，仅用179个标注查询即在多个信息检索基准上显著超越基线并媲美甚至超越GPT-4，尤其在推理密集型任务中表现突出。
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Thinking Out Loud: Do Reasoning Models Know When They're Right?
Published: at 11:51 AM 90.51 🤔本文通过对比指令微调、监督微调和强化学习训练的大型推理模型，发现推理导向训练显著提升了推理任务中的准确性和校准能力，但在事实性任务中可能削弱小规模模型对知识边界的感知。
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Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
Published: at 11:32 AM 90.51 🤔本文通过对92个开源语言模型的元分析，提出了一种超越缩放定律的性能预测框架，揭示了数据组成（如代码比例15-25%）和架构决策对下游任务性能的显著影响，预测精度相对提升3-28%。
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Self-Tuning: Instructing LLMs to Effectively Acquire New Knowledge through Self-Teaching
Published: at 11:12 AM 90.50 🤔本文提出SELF-TUNING框架，通过自教策略（SELF-TEACHING）显著提升大型语言模型从新文档中获取知识的能力，并在记忆、提取和推理任务上取得优异表现，同时保持较好的知识保留能力。
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RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
Published: at 11:16 AM 90.48 🤔本文提出RL-of-Thoughts (RLoT) 方法，通过强化学习训练轻量化导航模型，在推理时动态构建任务特定逻辑结构，显著提升大型语言模型在多领域推理任务中的表现，并展现出跨模型和任务的强迁移能力。